Scale Dependencies and Self-Similarity Through Wavelet Scattering Covariance. - Rudy Morel; Gaspar Rochette; Roberto Leonarduzzi; Jean-Philippe Bouchaud; Stéphane Mallat (CoRR, 2022)

Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data. - Ali Siahkoohi; Rudy Morel; Maarten V. de Hoop; Erwan Allys; Grégory Sainton; Taichi Kawamura (ICML, 2023)

Martian time-series unraveled: A multi-scale nested approach with factorial variational autoencoders. - Ali Siahkoohi; Rudy Morel; Randall Balestriero; Erwan Allys; Grégory Sainton; Taichi Kawamura; Maarten V. de Hoop (CoRR, 2023)

Scattering Spectra Models for Physics. - Sihao Cheng; Rudy Morel; Erwan Allys; Brice Ménard; Stéphane Mallat (CoRR, 2023)

Compact models of multi-scale processes. (Modèles compacts de processus multi-échelles). - Rudy Morel (2023)

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning. - Ruben Ohana; Michael McCabe; Lucas Meyer; Rudy Morel; Fruzsina J. Agocs; Miguel Beneitez; Marsha Berger; Blakesley Burkhart; Stuart B. Dalziel; Drummond B. Fielding; Daniel Fortunato; Jared A. Goldberg; et al. (NeurIPS, 2024)

Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task. - Siavash Golkar; Alberto Bietti; Mariel Pettee; Michael Eickenberg; Miles D. Cranmer; Keiya Hirashima; Géraud Krawezik; Nicholas Lourie; Michael McCabe; Rudy Morel; Ruben Ohana; Liam Holden Parker; et al. (CoRR, 2024)

DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction. - Rudy Morel; Jiequn Han; Edouard Oyallon (CoRR, 2025)